This is a metric that ranges from negative infinity to 1. It is a measurement that explains how much variance in the y value can be determined by x variables. The closer to 1, the more variance in y can be explained by x. Or in other words the closer to 1, the more likely it is that you have feature important variables that would lead to accurate predictions on y because the features explain variance or changes in y.

R^{2} is a unitless measure of correlation of the features to the target.