Correlation: It measures the strength or degree of relationship between two variables. It doesn’t capture causality. It is visualized by a single point.
Regression: It measures how one variable affects another variable. Regression is all about model fitting. It tries to capture the causality and describes the cause and the effect. It is visualized by a regression line.