Outlier Analysis is a statistical technique used to identify data points that deviate significantly from the majority of a dataset, often indicating variability in measurement, experimental errors, or novel discoveries. It plays a crucial role in data cleaning, fraud detection, and anomaly detection, helping analysts to understand the underlying patterns and causes of these deviations.