I'm looking through a slide deck (slide 9) about Gaussian Processes, and I came to a slide that describes one example of a covariance function: Matérn $\frac{3}{2}$ Covariance.
$$C(x_1,x_2) = (1+\sqrt{6}\frac{|x_1-x_2|}{\ell})*\exp(\sqrt{6}\frac{|x_1-x_2|}{\ell})$$
where
$\ell>0$ is the "correlation length parameter" and
$\sigma^2>0$ the variance parameter (though this isn't in the formula which confuses me).
Then they show a graph like this:
You can see that changing $\ell$ changes the shape of the function. However, my understanding is that covariance requires two random variables/vectors as inputs. So, what is $x$ (on the x axis) of the graph referring to in this case?