[…] these sorts of problems break down into two types: *regression* problems, in which you need to *predict* some number, such as weight, given a bunch of other numbers, such as height; and *classification* problems, in which you need to *assign a label*, such as spam, given a bunch of numbers, for examples word counts for spammy words such as “viagra” and “cialis”.

Machine Learning for Hackers, Drew Conway, John Myles White, 2012.

The term “regression” was coined by Francis Galton in the nineteenth century to describe a biological phenomenon. The phenomenon was that the heights of descendants of tall ancestors tend to regress down towards a normal average (a phenomenon also known as regression toward the mean). For Galton, regression had only this biological meaning, but his work was later extended by Udny Yule and Karl Pearson to a more general statistical context.

From Wikipedia