Vector Autoregression (VAR) is a statistical model used to capture the linear interdependencies among multiple time series, allowing each variable to be a function of its own past values and the past values of all other variables in the system. It is particularly useful for forecasting and understanding the dynamic impact of shocks in systems where variables influence each other over time.