El fractal que estamos hablando es el conjunto de Julia para el polinomio $z \mapsto z^2 +c$. Si $f:\Bbb{C} \rightarrow \Bbb{C}$ es este polinomio, el conjunto $K(f) \subset \Bbb{C}$ es definida de la siguiente manera: $$K(F) = \{x |\lim_{n\to\infty} |f^n(x)| < \infty \}$$
where $f^n$ denotes the $n$th composition of $f$, that is $f \circ f \circ \dots \circ f(x)\,\, n $ times.
The Julia set, $J(f)$ which has far more exciting properties and is a little easier to calculate is simply $\partial K(f)$ the boundary of $K(x)$. The 'why' of this set forming a fractal for $c \neq 0$ is quite challenging and I can't go into that here. I will however refer you to a number of excellent resources that will help you. The book that requires pretty light prerequisites and is spectacular in regards to the geometry of fractals is this one by Kenneth Falconer. The best monograph on the subject of complex dynamics is that of Milnor, here.
But I digress now back to the subject of how to draw the Julia set for $z \mapsto z^2 +c$. The first method I will describe is the most straightforward. Idiomatically it goes like: for each pixel iterate $f$ and if it goes outise of the circle with radius 2, then color it some color depending on the number of iterations it takes to escape this circle, otherwise color it black. Here is my mathematica code for this:
f[z_] := z^2 - 0.53 - 0.53*I;
bailOut = 50;
test[z_] := Abs[z] <= 2;
JuliaCount[z0_] := Length[NestWhileList[f, N[z0], test, 1, bailOut]];
DensityPlot[JuliaCount[x + I*y], {x, -1.6, 1.6}, {y, -1.2, 1.2},
AspectRatio -> Automatic, Mesh -> None, PlotPoints -> 1000,
ColorFunction -> (If[# == 1, RGBColor[0, 0, 0], Hue[#]] &)]
which produces the following image, albeit very slowly:
If we want to make this faster, there are some interesting properties of Julia sets for polynomials that we can use in order to draw them with more reasonable computation. I'm going to list some watered down versions of the facts we'll need here and reference you to the Falconer book if you want more details and information.
$$1.\quad J(f^n) = J(f) \text{ y } J(f) \text{ es un repelente de conjunto fijo de } f\\
2.\quad \text{órbitas Periódicas de } f \text{ son densos en} J(f)\\
3.\quad J(f) = \parcial E(f), \text{ los puntos que se escapan al infinito}\\
4. \quad J(f) \text{ es atraer a un conjunto estable de } f^{-1}
$$
Using these facts and basic properties of $f$, it should be easy to see that if we apply $f^{-1} : z \mapsto \sqrt{z-c} $ to some point outside of the circle of radius 2, we will eventually get a point arbitrarily close to $J(f)$ and successive iteration will 'likely' produce many points far within one pixel of the of the set. So if we pick 10 points at random outside of the circle with radius 2, and perform the following idiomatic algorithm on them, we should get a nice drawing of the Julia set:
Perform $f^{-100}$ on $s_0$, the first starting point. Call this point $a_0$.
Color this point, as well as $f^{-1}(a_0) = a_1$, $f^{-1}(a_1) = a_2$ and so on for some number of iterations.
Repeat for other $s_i$ on the same drawing to get a picture of $J(f)$.
Esto debería producir un cuadro similar, con la importante diferencia de que no va a ser de color y por lo tanto, probablemente no será tan bonito.