Autocorrelation is essential in time series analysis as it helps detect patterns and dependencies within the data. By examining the autocorrelation function, we can identify seasonality, trends, and other recurring patterns in the time series. Autocorrelation is widely used in forecasting, anomaly detection, and identifying underlying dynamics in the data.