Time complexity measures the amount of time an algorithm takes to run as a function of its input size. Common time complexities include:
O(1): Constant time (e.g., accessing an element in an array by index).
O(log n): Logarithmic time (e.g., binary search in a sorted array).
O(n): Linear time (e.g., iterating through an array).
O(n^2): Quadratic time (e.g., nested loops).