By "Best Fit" we mean it is the line which has the minimum sum of squares distance from the points. 

By the sum of squares of the distances means we want the line so that when we sum the squares of the distances between our data points and the line it is a small as possible. Illustrated below

You may be asking why we don't just try and minimize the the sum of the distances... the math turns out to be simpler when we square.