This beta shows how much your dependent variable increases when your gender variable increases by one unit. For example if you have coded gender as female being 0 and male 1 then males would have that much higher response in average.
Additionally, although this might be practically unimportant in your case, if you have no other IV, regressing the outcome variable only on gender provides you with the average outcome of the base category of your gender variable with the intercept of the model, and the difference to that intercept with the regression coefficient of your gender variable.
y = 3 - 1*Gender would mean that for your base category of gender (Gender = 0), the average of your outcome variable is 3, and for Gender = 1, the average of the outcome variable is 2 (3 - 1). Regression tells you whether this difference is significant.
If you have other control variables, this would be a bit more complex. See here for a very easy and basic introduction: http://www.theanalysisfactor.com/interpreting-regression-coefficients/
Hope this helps.
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