Hierarchical regression is a statistical method used to understand the relationship between variables by adding predictors in steps, allowing researchers to see the incremental value of each set of predictors. This approach helps in examining how blocks of variables contribute to the explained variance in the dependent variable, controlling for previously entered blocks.