Big O Notation is a mathematical concept used in computer science to describe the efficiency of algorithms. It provides a way to express the upper limit of an algorithm's running time or space requirements in relation to the size of the input data. This helps developers understand how an algorithm will perform as the input grows. The notation uses symbols like O(n), O(log n), and O(n^2) to categorize algorithms based on their growth rates. For example, O(n) indicates a linear relationship, while O(n^2) suggests that the time or space needed increases quadratically with the input size.