Cubic interpolation is a mathematical method used to estimate values between known data points. It uses cubic polynomials to create a smooth curve that passes through these points, providing a more accurate representation than linear interpolation, which connects points with straight lines. This technique is commonly applied in fields like computer graphics, data analysis, and image processing. In cubic interpolation, the algorithm considers not just the nearest points but also the surrounding ones, ensuring that the resulting curve is smooth and continuous. This approach helps in reducing errors and improving the quality of the interpolated data, making it useful for applications such as signal processing and scientific simulations.