Granger Causality is a statistical hypothesis test used to determine if one time series can predict another. It is based on the idea that if a variable X Granger-causes variable Y, then past values of X should contain information that helps predict future values of Y, beyond what is already known from past values of Y alone. This concept is widely used in fields like economics, finance, and neuroscience to analyze relationships between variables over time. However, it is important to note that Granger causality does not imply true causation; it only indicates a predictive relationship based on historical data.