ARIMA is a popular statistical method used for analyzing and forecasting time series data by capturing various temporal structures through differencing, autoregression, and moving averages. It is particularly effective for datasets where the data points are not independent and identically distributed, allowing for accurate predictions by accounting for trends, seasonality, and noise.