What do you understand by the term Normal Distribution?
A normal distribution is a distribution that is solely dependent on two parameters of the data set: mean and the standard deviation of the sample.
 Mean — This is the average value of all the points in the sample that is computed by summing the values and then dividing by the total number of the values in a sample.

Standard Deviation — This indicates how much the data set deviates from the mean of the sample.
Ref: https://medium.com/fintechexplained/everwonderedwhynormaldistributionissoimportant110a482abee3#:~:text=A%20normal%20distribution%20is%20a,the%20values%20in%20a%20sample.
The normal (or Gaussian) distribution is one particular kind of a bell shaped curve. It is unimodal (that is, there is one peak"), symmetric (that is you can flip it around its mid point) and its mean, median and mode are all equal. However, it is only one such distribution  others meet all those conditions and are not normal.
Example would be the average IQ level. From the graph below, you can see that most people have an IQ score that is at or around the average. A few people score very high and a few score very low, which gives it the “tails” at both ends of the graph. You can see it has the famous Bellcurve shape.