Numerical stability refers to how errors in calculations can affect the results of numerical algorithms. When performing mathematical operations, small inaccuracies can accumulate, leading to significant deviations from the true answer. This is particularly important in fields like computer science, engineering, and scientific computing, where precise results are crucial. A stable algorithm maintains accuracy even when subjected to small perturbations or rounding errors. In contrast, an unstable algorithm may produce wildly incorrect results due to these minor inaccuracies. Understanding numerical stability helps in selecting appropriate methods for solving problems and ensures reliable outcomes in computations.