The relationship between two variables captured in the correlation coefficient (i.e., r) implies a linear or "straight line" relationship. 

Linear regression is the process of finding the best linear equation that provides a "linear model" of the relationship between the two variables. In other words, it draws the "best" straight line through the relationship.