Time Complexity is a concept in computer science that measures the amount of time an algorithm takes to complete as a function of the length of the input. It helps in evaluating the efficiency of algorithms by providing a way to compare their performance. Time complexity is often expressed using Big O notation, which describes the upper limit of the running time in relation to the input size. Understanding time complexity is crucial for developers and engineers when designing algorithms, as it allows them to predict how an algorithm will scale with larger inputs. By analyzing time complexity, one can identify potential bottlenecks and optimize code to improve performance, ensuring that applications run efficiently even with increasing data sizes.