Normalization is a crucial technique in data science and machine learning that involves rescaling data to a standard range, typically between 0 and 1. This process enhances the performance of algorithms by ensuring that no single feature dominates due to its scale. For instance, when working with datasets containing variables with vastly different ranges, such as income and age, normalization helps to level the playing field, allowing algorithms to interpret the data more effectively. By transforming the data into a uniform scale, normalization improves model interpretability and accuracy, making it an essential step in data preprocessing.