The multiple comparisons problem arises in statistical analysis when multiple hypotheses are tested simultaneously, increasing the likelihood of incorrectly rejecting at least one true null hypothesis (Type I error). To mitigate this risk, adjustments such as the Bonferroni correction or False Discovery Rate control are often applied to maintain the overall error rate at a desired level.