The Kolmogorov-Smirnov test is a statistical method used to compare two distributions or to assess if a sample follows a specific distribution. It measures the maximum difference between the cumulative distribution functions (CDFs) of the two datasets. This test is non-parametric, meaning it does not assume a specific distribution shape, making it versatile for various applications. In practice, the Kolmogorov-Smirnov test helps determine if two samples come from the same population or if a sample fits a theoretical distribution, such as the normal distribution. It provides a p-value to indicate the strength of the evidence against the null hypothesis, guiding decision-making in statistical analysis.