Directional dependence refers to the relationship between variables where the effect of one variable on another is contingent upon the direction of the relationship, often implying causality or influence in a specified direction. It is crucial in fields like statistics, physics, and machine learning to understand how changes in one variable can predict or affect changes in another, potentially leading to more accurate models and predictions.