In reply to Ksharp.

It is a core concept of probability theory. If F is any cumulative distribution and X is a random variable such that X ~ F, then F(X) ~ U(0,1). This is sometimes called the probability integral transformation. A copula is slightly different. It captures the dependence between two or more random variables. But you are correct that the probability integral transformation plays an important role in working with copulas.