O(n) describes linear time complexity, meaning the time taken grows linearly with the input size, while O(n^2) describes quadratic time complexity, where time grows proportionally to the square of the input size. An example of O(n) is a simple loop through an array, and an example of O(n^2) is a nested loop that iterates through the same array.