The multiple comparison problem arises when multiple statistical tests are conducted simultaneously, increasing the risk of incorrectly rejecting a true null hypothesis (Type I error). Addressing this issue often involves adjusting significance levels to control the family-wise error rate or the false discovery rate, ensuring more reliable results.