Making a hasty conclusion without considering all of the variables
X is true for A.
X is true for B.
Therefore, X is always true.
This fallacy, closely related to the anecdotal fallacy, occurs when a person takes an overly small sample size, sometimes a single example, and extrapolates a sweeping prediction based upon it. Small sample sizes run a high risk of being biased and are likely to not be representative of the whole. This is why stereotyping is frowned upon in both science and social life.
All three of your laborers are migrant workers. This country doesn’t even employ American farm workers anymore!
A sample size of three people isn’t going to be an accurate representation of every farm worker. Even if every employee on the specific farm were migrant, it is not safe to assume all farms in all regions are the same. For instance, this specific farm may be located close to the Mexican border, where farms in Iowa may employ a far larger number of local workers.
This fallacy, when using a single example, is sometimes referred to as the lonely fact fallacy or proof by example fallacy.