Quadratic Time Complexity O(nc):

The time complexity is defined as an algorithm whose performance is directly proportional to the squared size of the input data, as in nested loops it is equal to the number of times the innermost statement is executed. For example, the following sample loops have O(n2) time complexity

Quadratic time complexity, denoted as O(n^2), refers to an algorithm whose running time increases proportional to the square of the size of the input. In other words, for an input of size n, the algorithm takes n * n steps to complete the operation. An example of an O(n^2) algorithm is a nested loop that iterates over the entire input for each element, performing a constant amount of work for each iteration. This results in a total of n * n iterations, making the running time quadratic in the size of the input.
C++
// Here c is any positive constant
for (int i = 1; i <= n; i += c) {
for (int j = 1; j <= n; j += c) {
// some O(1) expressions
}
}

for (int i = n; i > 0; i -= c) {
for (int j = i + 1; j <= n; j += c) {
// some O(1) expressions
}
}