Quantile Transformation is a statistical technique used to map data to a uniform distribution by transforming each feature to follow a specified distribution, often a normal distribution. This method is particularly useful in machine learning to reduce the impact of outliers and ensure that different features have similar scales, improving model performance and convergence.