Multiple testing correction is a statistical method used to adjust the significance levels when conducting multiple hypothesis tests simultaneously, reducing the likelihood of falsely declaring results as significant. This correction is crucial in research fields with large datasets, such as genomics, to control the family-wise error rate or the false discovery rate, ensuring that findings are reliable and not due to random chance.