The median is the middle of the data. Half of the observations are less than or equal to it and half of the observations are greater than or equal to it. The median is equivalent to the second quartile or the 50th percentile.
For example, if the weights of five apples are 5, 5, 6, 7, and 8, the median apple weight is 6 because it is the middle value. If there is an even number of observations, you take the average of the two middle values.
The median is less sensitive than the mean to skewed data and extreme values. For data sets with these properties, the mean gets pulled away from the center of the data. In these cases, the mean can be misleading because the most common values in the distribution might not be near the mean.
For example, the mean might not be a good statistic for describing annual income. A few extremely wealthy individuals can increase the overall average, giving a misleading view of annual incomes. In this case, the median is more informative.