Why is correlation between my independent variables helping my linear regression model?
It seems that you are dealing with the problem of Multicollinearity. Multicollinearity happens when your predictors are correlated with other predictors in the model.

Moderate multicollinearity may not be problematic. However, severe multicollinearity is a problem because it can increase the variance of the coefficient estimates and make the estimates very sensitive to minor changes in the model. The result is that the coefficient estimates are unstable and difficult to interpret. 

You can use adjusted R-squared to see if the new added variable is actually helping your model to better explain the variance.