Divergence measures are mathematical tools used to quantify the difference between two probability distributions, often serving as a foundation for various applications in statistics, machine learning, and information theory. They are crucial for tasks such as hypothesis testing, model selection, and information retrieval, where understanding the discrepancy between distributions informs decision-making processes.