The Law of Large Numbers is a statistical principle that states as the number of trials or observations increases, the average of the results will get closer to the expected value. This means that if you flip a fair coin many times, the proportion of heads and tails will approach 50% as the number of flips increases. This law is important in fields like probability theory and statistics, as it helps to predict outcomes in large samples. It assures that random fluctuations will balance out over time, making it a key concept in understanding how averages behave in large datasets.