Technically, the central limit theorum refers to the characteristics of a sampling distribution.

Let's imagine we're looking at the heights of people in the population. There is a real value out there for the mean height, say, of British people. We could find it by measuring everyone, but to do so would be excessive. Instead, we take a random sample and measure the heights of those selected. The central limit theorum states that, for any collection of samples, the mean of the mean values for those samples will approach the mean of the population. (More samples will generally bring you closer to the true value.) Meanwhile, the distribution of those sample means will follow a classic bell curve distribution.

The fact that this is true for any population, whether the underlying distribution follows a unimodal, symmetric bell curve or not, is one of the most surprising and useful facts of statistics.