Null Hypothesis in Analysis and Testing
For your particular problem, the null hypothesis is

$H_0: \mu_{manifacturer} = \mu_{competitors}$

and the alternative hypothesis is 

$H_1: \mu_{manifacturer} &gt; \mu_{competitors}$.

Basically, the null hypothesis states that there is no difference between the widget under test and the widgets made by other competitors. The alternative hypothesis states that, instead, there is a difference and the widget under test is better than the widgets made by the competitors.

Now, in your statistical significance test, you are trying to determine if you can reject the null hypothesis, i.e, if the data can be used to demonstrate for a specific confidence level that the widget made by this manufacturer may be better than the ones made by the competitors on the market. Note that I wrote "may be". If you can not reject the null hypothesis on the basis of the available data, this is interpreted by saying that statistically the data do not provide enough evidence to support your assumption that the widget under test is better.

See this Wikipedia article and this one on Statistical hypothesis testing for additional information.